The Diversity of Model Tuning Practices in Climate Science.

Many examples of calibration in climate science raise no alarms regarding model reliability. We examine one example and show that, in employing classical hypothesis testing, it involves calibrating a base model against data that are also used to confirm the model. This is counter to the ‘intuitive p...

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Publicado en:Philosophy of Science Vol. 83; no. 5; pp. 1133 - 1145
Autores principales: Steele, Katie, Werndl, Charlotte
Formato: Artículo
Publicado: Cambridge University Press Dec2016
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Acceso en línea:Ver este registro en EBSCOhost
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        atl: The Diversity of Model Tuning Practices in Climate Science.
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          Steele, Katie
          Werndl, Charlotte
        affil:
          We are grateful for valuable discussion and suggestions from the anonymous referees as well as to the audiences at the PSA 2014, the 2015 Philosophy of Climate Science Conference at the University of Pittsburgh, the Theory Construction in Science Conference at the London School of Economics, the Philosophy Colloquium at the University of Groningen, the Philosophy of Science Seminar at Bristol University, the Colloquium in Mathematical Philosophy at the Munich Center for Mathematical Philosophy, the British Society for the Philosophy of Science Seminar, the 2014 Trends in Logic Workshop at Ghent University, and the Third Reasoning Club Conference at the University of Kent. Funding support for the research was provided by the Arts and Humanities Research Council and by the ESRC Centre for Climate Change Economics and Policy, funded by the Economic and Social Research Council. Katie Steele was also supported by a 3-month research fellowship in residence at the Swedish Collegium for Advanced Study.
          To contact the authors, please write to: Katie Steele, Australian National University
      su:
        Climatology
        Parameterization
        Climate change
        Surface temperature
        Statistical hypothesis testing
      sug:
        subj:
          Climatology
          Parameterization
          Climate change
          Surface temperature
          Statistical hypothesis testing
      ab: Many examples of calibration in climate science raise no alarms regarding model reliability. We examine one example and show that, in employing classical hypothesis testing, it involves calibrating a base model against data that are also used to confirm the model. This is counter to the ‘intuitive position’ (in favor of use novelty and against double counting). We argue, however, that aspects of the intuitive position are upheld by some methods, in particular, the general cross-validation method. How cross-validation relates to other prominent classical methods such as the Akaike information criterion and Bayesian information criterion is also discussed.
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